Normalization of DNA encoded library affinity selection results driven by high throughput sequencing and HPLC purification.

The output of an affinity selection screening results in a huge amount of valuable data that, after conducting the appropriate analysis, lead to the correct identification of the compounds enriched in the target of interest. The approach chosen to perform these analyses has become a key step in the development of a successful DNA Encoded Library platform. In this paper, we describe the combination of High Performance Liquid Chromatography purification during the library production with the Next Generation Sequencing analysis of the libraries to assess the yield of the chemical reactions prior to the affinity selection. This process allows us, apart from achieving higher quality libraries, to enable a normalization analysis of the affinity selection output, thus minimizing the bias induced by the chemical yield of each reaction as a misleading factor within the analysis and subsequent compound short-listing for off-DNA synthesis.

A novel phage display vector for selection of target-specific peptides.

Intrinsic low display level of polypeptides on phage is a fundamental and limiting hurdle in successful isolation of target-specific binders by phage display technology. To circumvent this challenge, we optimized the copy number of peptides displayed on the phage surface using type 33 phage vector. We randomized the first 67 amino acids of the wild type PIII to identify mutants that would result in its reduced expression. Consequently, the display level was improved by 30-fold due to higher incorporation of the synthetic PIII-peptide fusion protein on the phage surface. Utilization of this novel phage vector should provide a solid basis for the discovery of therapeutic peptides.

A Decoupled Automation Platform for Hydrogen/Deuterium Exchange Mass Spectrometry Experiments.

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) is a biophysical technique well suited to the characterization of protein dynamics and protein-ligand interactions. In order to accurately define the rate of exchange, HDX experiments require the repeated measure of deuterium incorporation into the target protein across a range of time points. Accordingly, the HDX-MS experiment is well suited to automation, and a number of automated systems for HDX-MS have been developed. The most widely utilized platforms all operate an integrated design, where robotic liquid handling is interfaced directly with a mass spectrometer. With integrated designs, the exchange samples are prepared and injected into the LC-MS following a "real-time" serial workflow. Here we describe a new HDX-MS platform that is comprised of two complementary pieces of automation that disconnect the sample preparation from the LC-MS analysis. For preparation, a plate-based automation system is used to prepare samples in parallel, followed by immediate freezing and storage. A second piece of automation has been constructed to perform the thawing and LC-MS analysis of frozen samples in a serial mode and has been optimized to maximize the duty cycle of the mass spectrometer. The decoupled configuration described here reduces experiment time, significantly improves capacity, and improves the flexibility of the platform when compared with a fully integrated system.

Two-Site Evaluation of the Repeatability and Precision of an Automated Dual-Column Hydrogen/Deuterium Exchange Mass Spectrometry Platform.

Hydrogen/deuterium exchange coupled with mass spectrometry (HDX-MS) is an information-rich biophysical method for the characterization of protein dynamics. Successful applications of differential HDX-MS include the characterization of protein-ligand binding. A single differential HDX-MS data set (protein ± ligand) is often comprised of more than 40 individual HDX-MS experiments. To eliminate laborious manual processing of samples, and to minimize random and gross errors, automated systems for HDX-MS analysis have become routine in many laboratories. However, an automated system, while less prone to random errors introduced by human operators, may have systematic errors that go unnoticed without proper detection. Although the application of automated (and manual) HDX-MS has become common, there are only a handful of studies reporting the systematic evaluation of the performance of HDX-MS experiments, and no reports have been published describing a cross-site comparison of HDX-MS experiments. Here, we describe an automated HDX-MS platform that operates with a parallel, two-trap, two-column configuration that has been installed in two remote laboratories. To understand the performance of the system both within and between laboratories, we have designed and completed a test-retest repeatability study for differential HDX-MS experiments implemented at each of two laboratories, one in Florida and the other in Spain. This study provided sufficient data to do both within and between laboratory variability assessments. Initial results revealed a systematic run-order effect within one of the two systems. Therefore, the study was repeated, and this time the conclusion was that the experimental conditions were successfully replicated with minimal systematic error.

Capillary electrophoresis and small molecule drug discovery: a perfect match?

Capillary electrophoresis (CE) is an analytical technique based on the separation of the analytes within a capillary owing to their different electrophoretic mobilities. It is widely used in pharmaceutical analyses owing to its versatility and high separation power. However, its penetration into the drug discovery scene has been relatively limited until recent years. Several factors have contributed to this low implementation, including the maturity of liquid chromatography, the scarcity of experienced CE practitioners, and certain limitations intrinsic to the technique. Recently, instrumental improvements and the growing demand for analytical information have lead to a continuously expanding range of routine electrophoretic applications throughout pharmaceutical discovery and development. In this article we review CE fundamentals, review well-established CE methodologies in drug discovery of small molecules and discuss trends that, in our opinion, might emerge in the coming years.

How well do lipophilicity parameters, MEEKC microemulsion capacity factor, and plasma protein binding predict CNS tissue binding?

Brain fraction unbound (Fu) is critical to understanding the pharmacokinetics/dynamics of central nervous system (CNS) drugs, thus several surrogate predictors have been proposed. At present, correlations between brain Fu, microemulsion electrokinetic chromatography capacity factor (MEEKC k'), plasma Fu, octanol-water partition coefficient (clogP), and LogP at pH 7.4 (clogD(7.4) ) were compared for 94 diverse molecules, and additionally for 587 compounds. MEEKC k' was a better predictor of brain Fu (r(2) = 0.74) than calculated lipophilicity parameters (clogP r(2) = 0.51-0.54, clogD(7.4) r(2) = 0.41-0.44), but it was not superior to plasma Fu (r(2) = 0.74-0.85) as a predictor of brain Fu. MEEKC k' did not predict plasma Fu(r(2) = 0.58) as well as brain Fu, and the extent of improvement over clogP or clogD(7.4) (r(2) = 0.41-0.49) was less pronounced. Although log-log-correlation analysis supported seemingly strong prediction of brain Fu both by MEEKC k' and by plasma Fu (r(2) ≥ 0.74), analysis of prediction error estimated a 10-fold and 6.9-8.6-fold prediction interval for brain Fu estimated using MEEKC k' and plasma Fu, respectively. Therefore, MEEKC k' and plasma Fu can predict the log order of CNS tissue binding, but they cannot provide truly quantitative brain Fu predictions necessary to support in-vitro-to-in-vivo extrapolations and pharmacokinetic/dynamic data interpretation.

Application of LC/MS and related techniques to high-throughput drug discovery.

The broad coordinated implementation of common platform technologies, such as LC/MS, can be a key factor in attaining increased throughput, sensitivity and data quality for pharmaceutical discovery. These platform technologies are the key tools that Medicinal Analytical Chemists rely upon to address the ever-changing needs of a drug discovery team. Despite the recent advances in key areas of sensitivity and speed for LC/MS, additional progress to address these never-ending analytical problems can be anticipated. This review will highlight current status and future advances for the applications of LC/MS and related techniques to high-throughput drug discovery.

Liquid chromatography-mass spectrometry and related techniques for purity assessment in early drug discovery.

The combination of HPLC and MS has become the most valuable analytical tool to determine the identity and purity of a drug substance in the drug discovery arena over the past decade. This article describes different LC/MS configurations and their broad applicability to meet the fundamental analytical requirements involved in discovering new drugs. In addition, the value of chemiluminescence nitrogen detection for absolute purity determination and the convenience of CE as an orthogonal separation technique to HPLC are also discussed. In summary, LC/MS-based methodologies that implicate automation, various levels of throughput and open access systems have proved to be an integral part of the drug discovery process. As a result, the paradigm of high-quality/-quantity information is fulfilled in a timely fashion.